Brain scans reveal how personalized social media content may amplify negative moods

A study published in Computers in Human Behavior reveals that personalized social media content from algorithms may negatively impact mental health. Researchers from The University of Texas at Dallas assessed 60 young adults using depression and anxiety scales and monitored their brain activity while they watched two sets of videos: personalized recommendations from their Instagram or TikTok accounts, and general trending videos.

Using EEG, they measured frontal alpha asymmetry, a measure of emotional processing and motivation. Left-sided dominance indicates positive emotional processing, while right-sided dominance is linked to negative processing and withdrawal-related behaviors. The study found that participants with higher depressive symptoms were shown more depressive content in their recommendations, and their brain activity was indicative of depression, unlike their activity while watching trending videos.

This pattern suggests that if a person is already feeling depressed, the algorithms reflect that, leading to a negative feedback loop. Participants' devices were used as-is, without researchers selecting videos. The study emphasizes the importance of understanding how social media consumption affects individuals and aims to develop healthy engagement behaviors to prevent negative mood amplification.

Researchers suggest educating users on curating positive content and limiting exposure to negative videos. Parents are encouraged to be aware of algorithmic influences on mood, rather than simply limiting their teens' screen time.